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Machine Learning: End-to-End guide for Java developers

You're reading from   Machine Learning: End-to-End guide for Java developers Data Analysis, Machine Learning, and Neural Networks simplified

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Product type Course
Published in Oct 2017
Publisher Packt
ISBN-13 9781788622219
Length 1159 pages
Edition 1st Edition
Languages
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Authors (2):
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Krishna Choppella Krishna Choppella
Author Profile Icon Krishna Choppella
Krishna Choppella
Uday Kamath Uday Kamath
Author Profile Icon Uday Kamath
Uday Kamath
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Toc

Chapter 3. Unsupervised Machine Learning Techniques

In the last chapter, we focused on supervised learning, that is, learning from a training dataset that was labeled. In the real world, obtaining data with labels is often difficult. In many domains, it is virtually impossible to label data either due to the cost of labeling or difficulty in labeling due to the sheer volume or velocity at which data is generated. In those situations, unsupervised learning, in its various forms, offers the right approaches to explore, visualize, and perform descriptive and predictive modeling. In many applications, unsupervised learning is often coupled with supervised learning as a first step to isolate interesting data elements for labeling.

In this chapter, we will focus on various methodologies, techniques, and algorithms that are practical and well-suited for unsupervised learning. We begin by noting the issues that are common between supervised and unsupervised learning when it comes to handling...

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